“紫色砂、页岩岩性特征”颜色修订建议——基于四川紫色土母岩颜色特征

四川是我国紫色砂、页岩分布最具代表性的地区。利用《中国标准土壤色卡》(以下简称中国色卡)、日本《新版标准土色贴》(以下简称日本色卡)和分光测色计采集了四川45个典型紫色土母岩样品的颜色信息,并与《中国土壤系统分类检索(第三版)》中"紫色砂、页岩岩性特征"的紫色(RP)定义进行了比对,在此基础上提出了相关的修订建议。结果表明,用中国色卡和日本色卡对母岩岩块测色时,符合RP色调的样品分别占20.0%和33.3%;而对母岩粉末测色时,仅中国色卡有2.2%的样品符合RP色调;用分光测色计对母岩岩块及粉末的测色结果则均无RP色调,绝大部分为YR色调。因此,结合他人对紫色及红色的定义等,建议将"紫色砂、页岩岩性特征"的颜色修订为:色调为2.5RP～10RP;或色调为2.5R～5YR,干态明度为3～6,干态彩度为2～4。按修改后的标准,有62.2%～75.6%的样品符合紫色定义,这一结果更符合对紫色土颜色的传统认识。此外,建议进一步完善土壤色卡系统,或使用可客观、准确、自动读取Munsell颜色信息的便携式测色仪来测量土壤颜色;野外调查时对"紫色土"要注意观测土壤中紫色砂、页岩碎屑"紫色"区域的颜色,以防忽略有"紫色砂、页岩岩性特征"的土壤。     

新编《中国土壤色卡》即将发行

由中国科学院南京土壤研究所和中国科学院西安光学机械研究所根据我国土壤特点联合研制的《中国土壤色卡》将于年底问世。这是我国第一本比较完整的、可供土壤、自然地理、地质和考古工作者描述土壤、沉积物、沉积岩等颜色用的标准芒塞尔色卡。色调页和色片数量超过国外同类芒塞尔土色卡,共有15张色调页,28种色调,423个色片。该色卡采用国内先     

测色仪与中国标准土壤色卡测定土壤颜色比较——以川中丘陵区为例

Munsell色卡是测定土壤颜色的传统工具,而测色仪是测定土壤颜色的新兴仪器。利用统计参数及相关颜色差异等级,比较2种原理、价格不同的测色仪测定川中丘陵区27个拟定土系共97个过2 mm筛风干土壤Munsell颜色与利用《中国标准土壤色卡》目测(即目测法)的差异。结果表明,川中丘陵区风干土壤色调集中于YR色调,未出现RP色调,明度较高,彩度较低。2种测色仪均较目测法测定土壤Munsell颜色色调偏黄,但明度、彩度较一致;以目测值为参照,CM600d实测值和Nix校正值的色调、明度、彩度均方根误差(RMSE)分别为1.74、0.98、0.97和2.04、0.57、0.88,与目测差异等级为"微弱"、"明显"和"强烈"数量分别为90.72%、8.25%、1.03%和84.54%、14.43%、1.03%,表明使用2种测色仪均能辅助研究者判别土壤颜色,提高土壤颜色判别精确度,Nix测定土壤Munsell颜色明度更接近目测,且更具价格优势。     

《中国标准土壤色卡》中芒塞尔颜色系统的建立

对《中国标准土壤色卡》研制工作中建立我国土壤色卡颜色系统的依据进行了论述。对现有的国外同类土壤色卡进行了分析比较得出了结论。给出了研究工作中全部色调的色差结果，讨论这了套色卡的特点。这套色卡具有中国特色，可以满足测定和描述我国土壤颜色的需要。     

基于PLSR的土壤颜色预测方法及其与色系转换法的对比研究

传统的土壤颜色测定主要采用蒙塞尔比色卡比对,精度高,但费时费力。近年来尝试采用色系转换法预测土壤颜色,方法较为简便。基于土壤高光谱反射率和偏最小二乘回归(PLSR)方法进行土壤颜色预测,并与色系转换法进行对比研究。采集皖赣鄂交界地区76个不同颜色的土壤样品,分别采用PLSR及色系转换法进行土壤颜色预测,并与实测结果进行了对比。结果表明,PLSR交叉验证的R2cv分别达到0.62、0.61和0.75,测定值标准偏差与标准预测误差的比值(RPD)分别达到1.94、1.67和2.15,说明PLSR模型用于土壤颜色预测是可行的;其均方根误差(RMSE)仅为1.32、0.55和0.97个单位,较色系转换法的RMSE分别低0.94、1.24和0.95个单位,其HV/C整体预测误差?E的平均值为1.91,较色系转换法的平均值低5.16,说明PLSR方法预测土壤蒙塞尔颜色较色系转换法更优。该方法为土壤颜色的获取提供了一种新的途径。     

四川盆地沙溪庙组地层(J2s)岩石发育土壤的系统分类研究

地理发生分类的紫色土在中国土壤系统分类中的归属一直受到高度关注,以四川盆地分布最为广泛的侏罗系沙溪庙组地层岩石发育的土壤为研究对象,在对19个典型剖面的成土条件、剖面形态特征和土壤理化性质分析的基础上,根据《中国土壤系统分类检索(第三版)》,确定了供试土壤的诊断层和诊断特性及其在中国土壤系统分类中的高级类别。结果表明,供试土壤归属于3个土纲、3个亚纲、7个土类和12个亚类;色卡确定的颜色上满足“紫色砂、页岩岩性特征”的剖面仅7个;但若在原颜色定义上增加“或色调为2.5YR~5YR,干态明度为4~6,干态彩度为3~4”条件,则有11个剖面的色卡定色符合“紫色砂、页岩岩性特征”,3个剖面的仪器定色符合该特征。     

初评《中国土壤系统分类(首次方案)》

作者认为,《中国土壤系统分类(首次方案)》一书,以土壤发生学理论为指导,以土壤单元的诊断层和诊断特性为基础所制定的土壤系统分类制,既吸收了国外的先进经验又具有中国特色。从完善中国的土壤系统分类制出发,作者提出了需要进一步考虑的问题:亚类划分依据和标准;诊断层和诊断特性的选择和过渡土类的地位。     

基于图像处理的冬小麦氮素监测模型

为探索基于数字图像处理技术的冬小麦氮素无损诊断图像评价指标及构建方法,设计拍摄2012-2014年度不同种植方案下冬小麦冠层图像,基于归一化的H分量K均值聚类分割算法提取基础颜色特征值,与同期叶片氮含量(leaf nitrogen content,LNC)进行线性拟合,调优并确定三原色分量最佳拟合系数,提出RGB空间下的颜色组合标准化指数(normalized color mix index,NCMI)。对比深绿色指数(dark green color index,DGCI)、红光标准化值(normalized redness intensity,NRI)和绿光与红光比值G/R发现,3个采样期NCMI与LNC的决定系数R~2均高于3个对比指标,分别为0.77、0.79、0.94,均方根误差(root mean square error,RMSE)相较同期最低的指标,分别降低了0.18%、0.37%和1.67%;生选6号和扬麦18号NCMI与LNC的相关性,在一定冠层覆盖度下均优于其他3个指标;D2密度(3×106株/hm~2)N1(纯氮150 kg/hm~2)处理下NCMI效果明显优于其他3个指标,R~2和RMSE较NRI分别改善了7.69%和4.11%,该研究可为一定冠层覆盖度下的冬小麦氮素营养诊断图像评价指标提供参考。     

《黄土丘陵沟壑区种子库研究》

正《黄土丘陵沟壑区种子库研究》一书由中国科学出版社于2015年10月出版。该书是焦菊英研究员及其团队自2003年以来,对国家自然科学基金面上项目"黄土丘陵区退耕地植被恢复与土壤环境的互动效应"(40271074)、"黄土高原退耕地植被恢复对土壤侵蚀环境的响应与模拟"(40571094)、"黄丘区土壤种子库分布格局及植被恢复的土壤侵蚀解释"(40771126),及国     

鄱阳湖流域日降雨的侵蚀性雨量标准研究

确定日降雨的侵蚀性雨量标准是提高基于日降雨数据的降雨侵蚀力模型计算精度的重要前提。利用鄱阳湖流域降雨数据,采用最小偏差法,确定该流域日降雨的侵蚀力雨量标准。结果表明:(1)鄱阳湖流域次降雨的侵蚀性雨量标准为14.0 mm,降雨侵蚀力偏差系数为1.8%,土壤侵蚀损失率2.8%,降雨场次错选度为14.9%。(2)流域内各站点的逐月降雨量均表现为6月达到峰值的倒"V"形规律;侵蚀性次降雨中,降雨时间跨越2日或以上的类型最多,占总次数的54.2%。(3)流域日降雨的侵蚀性雨量标准为10.0 mm,该标准下年均次、日降雨侵蚀力偏差值为0.11%。     

基于Landsat-8数据的土壤颜色预测方法研究

选择黑龙江省292个自然风干土壤样品,室内测定土壤高光谱反射率,然后依据三刺激值法计算土壤CIE XYZ色彩空间各颜色分量,用于土壤颜色预测和验证.同时,提取各样品采集点位的Landsat-8 OLI原始反射率数据,计算归一化差值植被指数、归一化差值水体指数、归一化差值湿度指数、归一化差值不透水面指数,并据此提出建模光...     

A Comparative Review of Methods of Using Soil Colors and their Patterns for Wetland Ecology and Management

Soil color patterns are essential to understand hydrologic regime and biogeochemical processes in wetland ecosystems. Munsell Soil Color Chart (MSCC) has been traditionally and predominantly used to identify and quantify hydric soil field indicators, but several simple, low-cost alternatives have become recently available to compare their efficacy in complementing the MSCC in soil color assessment. We conducted an intensive literature review on studies utilizing different methods to identify and quantify hydric soil colors and associated patterns; these include 1) the MSCC, 2) the Nix Color Sensor, 3) mobile phone camera (MPC) and medium-end digital camera photography, and 4) colorimetry and spectrometry. A review of these methods elucidates their respective strengths and weaknesses and highlights the importance of considering study-specific attributes in determining which method to choose for field studies of hydric soil colors. Redoximorphic features (RMFs) require methods capable of capturing small and heterogeneous soil surfaces and features such that the MSCC and digital photography are the most appropriate methods; on the other hand, the Nix Color Sensor provides rapid assessment of soil color that does not necessitate rigorous training to overcome biases that might come about in more subjective methods such as the MSCC. Overall, all alternative methods reviewed have their own merits and capacity to complement measurements made by the MSCC.     

Predicting Soil Organic Carbon and Total Nitrogen in the Russian Chernozem from Depth and Wireless Color Sensor Measurements

Color sensor technologies offer opportunities for affordable and rapid assessment of soil organic carbon (SOC) and total nitrogen (TN) in the field, but the applicability of these technologies may vary by soil type. The objective of this study was to use an inexpensive color sensor to develop SOC and TN prediction models for the Russian Chernozem (Haplic Chernozem) in the Kursk region of Russia. Twenty-one dried soil samples were analyzed using a Nix Pro? color sensor that is controlled through a mobile application and Bluetooth to collect CIEL*a*b* (darkness to lightness, green to red, and blue to yellow) color data. Eleven samples were randomly selected to be used to construct prediction models and the remaining ten samples were set aside for cross validation. The root mean squared error (RMSE) was calculated to determine each model’s prediction error. The data from the eleven soil samples were used to develop the natural log of SOC (lnSOC) and TN (lnTN) prediction models using depth, L*, a*, and b* for each sample as predictor variables in regression analyses. Resulting residual plots, root mean square errors (RMSE), mean squared prediction error (MSPE) and coefficients of determination (R², adjusted R²) were used to assess model fit for each of the SOC and total N prediction models. Final models were fit using all soil samples, which included depth and color variables, for lnSOC (R² = 0.987, Adj. R² = 0.981, RMSE = 0.003, p-value < 0.001, MSPE = 0.182) and lnTN (R² = 0.980 Adj. R² = 0.972, RMSE = 0.004, p-value < 0.001, MSPE = 0.001). Additionally, final models were fit for all soil samples, which included only color variables, for lnSOC (R² = 0.959 Adj. R² = 0.949, RMSE = 0.007, p-value < 0.001, MSPE = 0.536) and lnTN (R² = 0.912 Adj. R² = 0.890, RMSE = 0.015, p-value < 0.001, MSPE = 0.001). The results suggest that soil color may be used for rapid assessment of SOC and TN in these agriculturally important soils.     

不同空间范围土壤色度的纬向变化特征及其气候意义

对不同气候条件下发育的土壤/古土壤进行色度分析,探讨其色度参数的空间变化规律及其作为气候变化代用指标的可靠性。结果表明:(1)较小的空间尺度上,土壤色度参数变化复杂,与气候相关关系不显著。土壤色度参数在大空间尺度中均表现出一定的纬向变化,红度(a*)随纬度的增加而降低,黄度(b*)与纬度的拟合曲线趋近于开口向上的抛物线,黄度与红度的比值(b*/a*)随着纬度的增加近似呈线性增加。(2)土壤剖面色度参数均与气候因子(年均降水和年均温)具有一定的相关关系,b*/a*与年均温相关系数最大。色度参数a*与年均降水相关系数稍高于b*/a*,但a*易受其他因素影响;而土壤色度参数b*/a*对土壤颜色的空间变化敏感,是指示气候变化的适用指标。     

Soil colour: its measurement and its designation in models of uniform colour space

The principles of colour perception are outlined and applied to the problems of soil colour measurement using ‘Munsell Soil Color Charts’. As care is needed in using these charts to make an accurate assessment of soil colour, recommendations for the correct methods for soil colour measurement are outlined. The three soil colour characteristics of Munsell Hue, Value and Chroma are commonly used in multivariate analyses as orthogonal, equi-dimensional, linear variables that describe perceived colour space. Such an approach may be inappropriate because the angular separation of Hue and an approximately 2.5:1 scaling relationship between Value and Chroma should be accounted for in any model of perceived colour space. An appropriate and simple polar transformation of Munsell colour data is compared with some other coordinate systems for representing colour space, including the CIELAB system. This polar transformation is recommended for processing colour data in multivariate analyses.     

亚热带山地草甸土性态的变异及其在中国土壤系统分类中的地位

为了解我国亚热带地区山地草甸土性态的变化和成土特点,从福建、浙江、江西、安徽、湖南和贵州等省采集了20个代表性山地草甸土剖面,详细观察了土壤剖面形态特征,分析了土壤颗粒组成、有机质、阳离子交换量(CEC)、酸度、氧化铁形态和黏土矿物类型等指标,并从诊断分类的角度探讨了它们在中国土壤系统分类中的地位。结果表明:这一地区的山地草甸土表层有机质积累均非常明显,颜色普遍呈黑色和深褐色,土壤酸化明显,土壤氧化铁游离度多在40%以下,土壤CEC较高。但研究也发现,不同样点之间土壤的土体厚度、剖面构型、黏化状况、有机质垂直分布、氧化铁含量、矿物类型及其诊断层和诊断特性均有较大的差异。土体构型大致有Ah-C、Ah-Bw-C、Ah-Bt-C和Ah-G-C等4类。根据中国土壤系统分类的诊断标准,可把研究的20个剖面归并为均腐土、潜育土、淋溶土、雏形土和新成土等5个土纲,下续分为6个亚纲、10个土类和15个亚类。研究认为,在地理发生分类中笼统地把这些土壤归为一个土类存在边界不明确等问题。     

Soil moisture variability along transects over a well-developed gully in the Loess Plateau,China

Knowledge of soil moisture distributions in gullies, which are highly variable spatially and temporally, is important for both restoring vegetation and controlling erosion in them, but little attention has been paid to this spatio-temporal variability to date. Therefore, we examined soil moisture profiles and their variability along three transects traversing sidewalls of a well-developed gully with steep slopes in a hilly area of the Chinese Loess Plateau. We took intensive measurements at 20-cm intervals from 0 to 160 cm depth, using a portable time domain reflectometer, from September 3 to October 20 2009 and from April 5 to July 20 2010. The results indicate that the mean, standard deviation and coefficient of variation of moisture content vary with time, their responses to precipitation vary at different depths, and moisture content is most variable when mean values are moderate (15–20%). Revised fitting functions developed and introduced by Famiglietti et al. (2008) captured with confidence the relationship between spatial variability (SD and CV) and spatial mean of moisture content (RMSE ranging from 0.0015 to 0.0293). Soil moisture clearly varied along the transects, the vertical distribution of soil moisture differed in different seasons, and correlation analysis showed that soil texture influenced the variability of surface soil moisture more strongly than terrain attributes (except during distinct rainfall events, when this pattern reversed). The results presented here should improve understanding of spatio-temporal variations in soil moisture profiles in well-developed gullies in the Loess Plateau, and potentially elsewhere.     

基于Web的中国土种数据库

来源于第二次全国土壤普查汇总成果的中国土种数据库是目前最全面的全国性土壤数据库。它收录了20世纪80年代我国主要土种的分布、面积、性状、土地利用情况和生产性能等资料。自2000年以来,中国科学院南京土壤研究所开始建设基于Web的中国土种数据库,构造了一个包括地点与土壤类型的空间分布关系和依据中国土壤发生分类系统的分类层次关系的实体-关系(entity-relationship,E-R)数据模型,形成了具有2 473个土种典型剖面、8 751个发生层及物理化学性质的数据产品。该数据库可通过互联网广泛应用于土地退化评估、环境影响研究以及土壤碳储量研究,亦可作为基础数据指导农业生产。     

北疆绿洲不同盐分浓度梯度下土壤的生物活性及其功能多样性

土壤盐分类型与含量对土壤生物活性和功能结构多样性会产生重要影响。本文模拟新疆北疆典型硫酸盐盐土,通过设置不同盐分浓度梯度(3、6、10、20和40 g kg-1),研究了土壤5种主要功能酶、土壤微生物量和土壤呼吸等生物性状的变化特征。结果表明:过氧化氢酶、蔗糖酶、β-葡萄糖苷酶和多酚氧化酶4种酶对盐分梯度响应非常敏感,其中过氧化氢酶、蔗糖酶和β-葡萄糖苷酶这3种酶活性与盐分浓度呈负相关,当盐分浓度达到40 g kg-1时,以上3种酶分别较对照降低25.7%、69.6%、30.0%;在3~6 g kg-1盐分浓度范围,多酚氧化酶随盐分浓度而升高,但在10~40 g kg-1时却显著降低,表现出"低盐促进,高盐抑制"的效应;纤维素酶对盐分浓度变化不敏感。土壤盐分与微生物量和微生物商呈显著负相关,与土壤基础呼吸和呼吸商则显著正相关,如40 g kg-1的盐分浓度导致土壤微生物量和微生物商分别较对照降低73.0%和69.5%,呼吸商升高了6.4倍。土壤过氧化氢酶、蔗糖酶、土壤微生物量、微生物商和呼吸商等可作为硫酸盐盐土早期预警生物指标。在40 g kg-1的含盐量下土壤生物功能结构明显区别于其他处理,且多样性指数显著下降。